# Urdu Dependency Parsing and Treebank Development: A Syntactic and Morphological Perspective

arXiv: https://arxiv.org/abs/2406.09549 · HTML: https://mlsanity.com/paper/2406.09549/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 32 references that are in the map.
- First posted on arXiv 13 Jun 2024.

## Builds on (most cited first, 2 of 2)

- [Transition-Based Dependency Parsing with Stack Long Short-Term Memory](https://mlsanity.com/paper/1505.08075/) (2015)
- [Syntax Representation in Word Embeddings and Neural Networks -- A Survey](https://mlsanity.com/paper/2010.01063/) (2020)

## Abstract (arXiv)

Parsing is the process of analyzing a sentence's syntactic structure by breaking it down into its grammatical components. and is critical for various linguistic applications. Urdu is a low-resource, free word-order language and exhibits complex morphology. Literature suggests that dependency parsing is well-suited for such languages. Our approach begins with a basic feature model encompassing word location, head word identification, and dependency relations, followed by a more advanced model integrating part-of-speech (POS) tags and morphological attributes (e.g., suffixes, gender). We manually annotated a corpus of news articles of varying complexity. Using Maltparser and the NivreEager algorithm, we achieved a best-labeled accuracy (LA) of 70% and an unlabeled attachment score (UAS) of 84%, demonstrating the feasibility of dependency parsing for Urdu.